Par-ime Work, Wages and Produciviy: Evidence from Mached Panel Daa Alessandra Caaldi (Universià di Roma "La Sapienza" and SBS-EM) Sephan Kampelmann (Universié de Lille, CLERSE, SBS-EM) François Rycx (Universié Libre de Bruxelles, SBS-EM and IZA) Absrac Using deailed mached employer-employee panel daa for Belgium over he period 1999-2006, he auhors invesigae he relaionship beween working ime, wages and produciviy. More precisely, hey are among he firs o examine how changes in he proporions of shor and long par-ime workers affec he produciviy of firms (measured by he value-added per hour worked) and o es for he presence of produciviy-wage gaps. Their findings, conrolled for a large range of individual and firm characerisics and robus o various economeric issues (including ime-invarian unobserved firm heerogeneiy, endogeneiy and sae dependence), sugges ha long par-ime workers are significanly more producive han shor par-ime and full-ime workers. Their resuls furher indicae ha average hourly wages wihin firms do no significanly depend on he incidence of par-ime jobs. Overall, his leads o he conclusion ha shor par-ime workers are paid a heir marginal produciviy while long par-ime workers appear o be underpaid. Key words: Wages, produciviy, par-ime employmen, mached panel daa, GMM. JEL Codes: J22, J24, J31. * We would like o hank Saisics Belgium for giving access o he daa. The usual disclaimer applies. 1
1 INTRODUCTION In he pas wo decades, par-ime jobs have become a prominen feaure of many srucural changes ha occurred on European labour markes. For insance, par ime has been one of he main facors underpinning processes of labour marke flexibilizaion (Branine 1999; Edwards and Robinson 2000). Wha is more, par ime has risen sharply during he laes economic downurn. In an aemp o reain incumben workers, many firms have preferred o reduce working hours over layoffs (Employmen in Europe 2010). In oher words, par-ime arrangemens appear o funcion as a buffer during criical sages of he business cycle (OECD 2010). In ligh of his evoluion, an accurae undersanding of he differen repercussions of par-ime work has emerged as an increasingly salien problem. In paricular, he impac of reduced working hours on differen measures of labour marke performance is sill no properly undersood. In his paper we address he following quesions: i) Do par-ime workers differ from full-ime workers in erms of wages and produciviy oucomes?, and ii) Are par-ime workers paid a heir marginal produciviy? A growing lieraure examines he impac of working ime on workers wages. Empirical resuls ypically documen a significan gap beween hourly wages of par- and fullime workers. By and large, his gap has been aribued o subsanial heerogeneiy beween jobs and/or beween individuals (Hirsch, 2005; Manning and Perongolo, 2008). Ye, for some counries a significan fracion of his gap remains unexplained afer conrolling for observable heerogeneiy. This may poin o oher forms of labour marke inequaliy or discriminaion agains par-ime workers (Bardasi and Gornick 2008). Besides, few sudies have focused on produciviy differences beween full-ime and par-ime workers. In fac, he relaionship beween working hours and produciviy has no been clearly esablished: boh exan heory and empirical resuls are inconclusive (Branine 2003; Lewis 2003; Nelen e al. 2011). Finally, as far as we know, here are no sudies invesigaing wheher par-ime workers are paid a heir marginal produciviy using accurae informaion on boh wages and produciviy. The presen paper conribues o his lieraure by esimaing he effec of par-ime work on produciviy, wages and produciviy wage-gaps. More precisely, we are among he firs o examine how changes in he proporions of shor and long par-ime workers affec he produciviy of firms and es for he presence of produciviy-wage gaps. To do so, we use deailed longiudinal mached employer-employee daa covering he Belgian privae secor 2
over he period 1999-2006. Our daa offer several advanages. Firs, he panel provides accurae informaion on average produciviy and wages wihin firms (i.e. on he average value added per hour worked and he mean hourly wage) and allows o conrol for a wide range of worker and firm characerisics (such as educaion, age, occupaion, sex, ype of conrac, firm size, firm age and secor). Second, we are able o address imporan measuremen issues such as firm-level fixed unobserved heerogeneiy, endogeneiy of working ime and sae dependence of firm produciviy and wages. Hence, our daa allows us o ackle various poenial biases ha are no always accouned for in he exising lieraure. Finally, i should be emphasized ha he disincion beween shor and long par-ime work, oo ofen negleced in he lieraure, is an imporan feaure of our sudy (Hirsch 2005; Russo and Hassink 2008). Indeed, he repercussions of par-ime arrangemens on wages and produciviy are likely o differ subsanially according o wheher he individual is absen during much of he work week (e.g. an employee wih peripheral asks coming in only one or wo days a week) or wheher she is almos working full ime (e.g. an employee ha works like her full-ime colleagues during he enire week bu leaves he office on Friday noon). 2 REVIEW OF THE LITERATURE 2.1 Theoreical background Economic heory advances several possible explanaions for differences in hourly pay and produciviy beween par-ime and full-ime workers. These explanaions can be grouped ino four main clusers ha are no muually exclusive bu raher end o overlap and reinforce each oher. The firs cluser of reasons perains o labour supply and demand ineracions, he argumen being ha some caegories of persons prefer o work par-ime raher han full-ime (and vice versa). This is paricularly saed o be he case wih regard o young workers (sudens), parens wih heavy home responsibiliies and older workers, all of whom may be seen o have a more marked preference for par-ime employmen and, for his reason, accep wages lower han hose associaed wih full-ime employmen. Noe, neverheless, ha such preferences in erms of work hours may jus as well be consrained as free. However, differences in preferences for par-ime employmen are no enough o generae a par-ime wage penaly. In order for his o occur, workers mus be heerogeneous and i canno be ha employers are indifferen o he way hey schedule work hours among workers. Hence, only a mix of workers preferences, skill differences and employer preferences can generae a par- 3
ime wage penaly. However, hese same forces may also work in he opposie direcion. Flexible working hours and oher alernaives o he radiional full-ime work schedule have been shown o increase produciviy and, consequenly, also wages (Shepard e al. 1996). A par-ime wage premium is ypically observed in indusries ha face seasonal or flucuaing demand for or supply of heir oupu ha canno be managed hrough he carrying of invenories; employers hen consen o pay high wages during peak periods when produciviy is high o par-ime workers willing o work shor inensive shifs. Hence, if a firm has a paricularly high labour demand during shor inervals of ime, and workers prefer o work long hours a a srech raher han space ou his working ime, hen par-ime wages may exceed full-ime wages, as here is no enough labour supply o mee labour demand. A lack of geographical mobiliy may also conribue o he par-ime/full-ime wage gap. Ermisch and Wrigh (1991) sae ha par-imers are more srongly bound by spaial consrains because hey are less willing o pay high coss o commue o and from work he more so since hey are ofen jus secondary breadwinners in he household. Given his lack of labour supply elasiciy, he local labour marke is in he hands of firms pracising monopsonisic power. Led by heir raionaliy as profi-maximising economic agens, hey end o adjus par-ime wages downwards. The second cluser concerns he cos srucure of firms. The exisence of fixed coss including he adminisraive coss of mainaining records for each employee, recruimen and firing coss and any componens of fringe benefis ha are independen of hours worked means ha firms oal labour coss do no increase proporionally wih hours worked (Mongomery, 1988). As a resul, par-ime workers are relaively more cosly o firms and may herefore receive lower wages. I can also be argued ha par-ime workers may generae coordinaion problems, especially in firms where heir number is marginal in comparison wih full imers (Lewis 2003). Furhermore, while par ime can be easily managed in a Tayloris organisaion in which workers can be subsiued o each oher, jobs ha pu a greaer emphasis on ask-specific skills are more difficul o manage on a par-ime basis since oucomes such as he coninuiy of oupu or relaionships wih cusomers migh be negaively affeced (Bonamy and May 1997; Edward and Robinson 2004). In addiion, managers migh no always adjus correcly heir expecaions when employees are moving from full o par ime, hus influencing he effeciveness of flexible work arrangemen policies. For insance, working reduced hours migh ofen mean having o deal in a shorer ime wih wha effecively remains a full-ime workload (Edwards and Robinson 2000; Lewis 2001, 2003). 4
The hird cluser of facors ha can accoun for a par-ime wage penaly is direcly relaed o workers produciviy. Several heories relae produciviy o he number of hours worked. An argumen in one direcion is ha, due o sar-up effecs, produciviy rises slowly a he beginning of a working day. As a resul, he worker s produciviy during he las hour of work is above he average daily level of produciviy (Barzel, 1973). Hence, par-ime workers who work less hours are less producive and herefore paid lower wages. However, oher auhors cones his model and poin ou ha iredness associaed wih long working hours migh significanly influence work abiliy so ha par-ime workers migh perform beer han full imers (Brewser and al. 1994). In addiion, flexible working ime arrangemens and par-ime jobs migh allow individuals o make a beer use of he circadian rhyhm and may reduce he amoun of sress, hus increasing he correspondence beween heir abiliies and job requiremens, poenially leading o higher performance (Pierce and Newsrom 1983; Bales e al. 1999). The fourh cluser of issues is relaed o he insiuional seings in a specific region or counry. Several sudies have shown ha par-imers have a lower level of union membership (Riley 1997). In a heoreical paper by Skåun (1998), he higher demand for par-imers is explained by he individual bargaining process ha allows he firm o increase he surplus from he bargain. Hence, par-imers are paid less as hey have less power. Moreover, given he progressive ax srucure in some counries, par-imers, who by definiion earn a lower annual gross wage han full-imers, are axed less and, herefore, union bargaining will ofen lead o a lower hourly gross wage for par-imers han for full-imers (Koskela and Vilmunen, 1996). This is he effec of unions ending o reason in erms of ne wages. Indeed, unions will be less likely o push as hard for higher gross wages for par-imers han for full-imers as he former face a lower average ax rae. Also, he composiion of income and payroll axes may influence he wage difference beween full-ime and par-ime workers (Koskela and Schöb 1999). However, payroll axaion is also found o decrease he wage rae wih he number of hours worked. Vella (1993) argues ha he rue wage is held consan bu ha he hourly wage rae decreases and is replaced by fringe benefis ha are no axable. Finally, anidiscriminaion legislaion may also have a decisive effec on he exisence or no of a pay penaly. 5
2.2 Empirical background 2.2.1 The impac on wages A growing lieraure offers some empirical evidence on he relaionship beween par-ime work and wages. Bardasi and Gornick (2008), using micro-daa of 1995 from he Luxembourg Income Sudy, find he presence of an hourly par-ime pay penaly for women in a cross-counry comparison among Canada, Germany, Ialy, Sweden, he UK, and he US. Wih he excepion of Sweden, he resuls of heir analysis show ha conrolling for workers and job characerisics reduces he par-ime pay penaly, which is mainly aribued o occupaional componens and segregaion. However, par of he pay gap remains even afer conrolling for observable characerisics, which migh be aribued o some form of discriminaion or o unobservable differences beween full imers and par imers. Analogous resuls for he UK labour marke can be found in Manning and Perongolo (2008) who use pooled daa from he Labour Force Survey from 2001 o 2003 and show ha differences in he ypes of jobs and occupaional segregaion are he main facors explaining he hourly parime pay penaly among Briish women. Hirsch (2005) uses level and longiudinal esimaes of wages from he US Curren Populaion Survey (1995-2002) and observes ha he larges share of he hourly par-ime penaly can be ascribed o differences in workers and jobs characerisics and ha a grea par of he remaining gap poins o he heerogeneiy of workers. Once full conrols are included in he model, he finds ha he par-ime pay gap is very modes a he beginning of careers of men and women; i ends o increase o a cerain exen wih ime, a phenomenon ha migh sem from a defici of experience and human capial accumulaion of par imers. Similar paerns are described in Russo and Hassink 2008, who use he pooled waves from 1999 and 2001 of he Working Condiions Survey for he Duch labour marke. No hourly par-ime wage gap is found by Hardoy and Schone (2006). Using pooled daa for 1997 and 1998 from he Level of Living Surveys and conrolling for observed characerisics, hey record no wage differences beween female par and full imers in Norway and no evidence of sysemaic selecion bias. These paerns may be aribued o well-developed ani-discriminaion policies and srong employmen proecion. Rodgers (2004) develops a cross-secional analysis using he 2001 wave from he Household, Income and Labour Dynamics in Ausralia Survey and does no find significan hourly par-ime pay gaps for Ausralian workers once selecion ino ypes of employmen and worker- and jobspecific characerisics are conrolled for. Also Booh and Wood (2008), using a panel daa of 6
he firs four waves of he same survey (2001 2004), do no deec a par-ime penaly in Ausralia - in fac hey observe he opposie. Once unobserved individual heerogeneiy is aken ino accoun, hey find a pay premium for par-ime women and men. Among he hypohesized explanaions for such a pay premium hey cie he srucure of he Ausralian ax sysem and he possibiliy ha i is less likely for par-ime han for full-ime workers o do overime hours (which reduces measured hourly wages). They also sugges ha par imers migh be more producive han full imers due o he faigue effecs we menioned above. However, hese resuls should be inerpreed wih cauion given ha he Ausralian sudy does no include informaion on produciviy levels. Few sudies invesigae wage differenials among par and full imers on he Belgian labour marke. The analyses of Jepsen (2001) and O Dorchai e al. (2007), based on daa from he 1990s respecively from he Household Panel Survey and he Srucure of Earnings Survey, show ha he hourly wage gap beween par-ime and full-ime workers almos disappears afer conrolling for observables. This resul is aribued o he effecive proecion of par-ime workers by Belgian ani-discriminaion policies. 2.2.2 The impac on produciviy Empirical evidence on he difference beween par-ime and full-ime workers in erms of produciviy oucomes is quie scarce. Moreover, resuls seem conradicory and difficul o compare due o he diversiy in analyical mehods (Lewis 2003). Exan sudies rely boh on quaniaive and qualiaive analyses in which measures of produciviy range from objecive (e.g., sales and gross revenue) o subjecive indicaors of performance (e.g., employmen commimen and sress). Some analyses are in line wih he hypohesis ha par ime can be more effecive han full ime in improving workers performance and firm s produciviy. Hagemann e al. (1994), using a survey of 3,000 employees in five German companies from differen indusries, show ha: i) sandard par ime (i.e. employees working fewer hours per day) increases moivaion and reduces abseneeism; ii) cyclical par ime allows o manage peaks and roughs in demand more efficienly (e.g. in indusries such as ourism and banking); and iii) shif-based par ime migh exend firm operaing hours, leading o a more inense use of capial. Perry-Smih and Blum (2000) focus on family-friendly pracices. They apply uni- and mulivariae analysis of covariance using cross-secional daa from he Naional Organizaions Survey of U.S. firms and conrol for firm level characerisics, showing ha he higher he incidence of such pracices, he higher he level of perceived marke and organizaional performance, profis, 7
and sales growh. The analysis of Nelen e al. (2011) poins in he same direcion. They sudy a mached employer employee cross-secional daase of Duch pharmacies in 2008, applying inernal insrumenal variable analysis in order o assess causaliy and address poenial endogeneiy of employmen shares while conrolling for observable characerisics. Their resuls show ha he larger he share of par-ime employmen, he higher he firm produciviy when he laer is measured by he number of prescripions delivered o cusomers. Conversely, Arvaniis (2003) develops cross-secion esimaes on daa from a survey among Swiss enerprises in he business secor and finds ha par-ime work correlaes negaively wih sales per employee (he sudy conrols for echnology, workplace organizaion, and indusry affiliaion). The sudy of Branine (2003) is based on daa obained from a quesionnaire and inerviews from hospials in he UK, France, and Denmark and shows mixed resuls. Respondens saed ha, on he one hand, par ime work is usually associaed wih low abseneeism and less sress. On he oher hand, i is also associaed wih higher urnover, lack of coninuiy of he service, low employmen commimen, and relaively lower skills. The difficulies associaed wih managing a par-ime workforce have been recorded by Edwards and Robinson (2004). The laer sudy consiss in a qualiaive analysis of he UK nursing profession based on a quesionnaire submied o a sample of nurses and managers. Respondens claim ha among he main advanages of par ime work here is reenion of maure saff, less sress, coverage of peaks in demand, less abseneeism, and harder work. Among he disadvanages hey menion problems of communicaion, an increase in adminisraive coss, and overheads associaed wih raining and difficulies wih coninuiy of service. In addiion, par-ime nurses declare o be less saisfied han heir full-ime colleagues wih beer opporuniies as regards qualificaion and promoion. Similar paerns emerged in Edwards and Robinson's (2000) sudy ha presens a qualiaive analysis of he meropolian police service in he UK. Benefis from inroducing par ime are he reenion of experienced people who would oherwise exi he labour force (especially women) and an increase in job saisfacion and commimen. Disadvanages are worsened communicaion and service coninuiy as well as he marginalizaion of par-ime workers in erms of raining and promoion. Difficulies wih par-ime pracices are also documened in he case sudy of a London borough in 1995 by Sanworh (1999): inerviews reveal ha many par-ime workers fel ha hey were doing a full-ime job in par-ime hours since managers did no correcly adjus expecaions when workers moved from full o par ime. 8
Finally, some analyses do no find any significan effec of par-ime work on produciviy. Savrou (2005) uses daa of all secors of he economy for foureen EU member saes and esimaes logisic regressions wihou finding any evidence of a relaionship beween par ime and subjecive measures of performance (as assessed by he highes ranking corporae officer). Similarly, according o he regression analysis of Valverde (2000), who draws on daa from he Crane-E daase covering he manufacuring and service secors of welve counries, he effec of par ime on he repored gross revenue of companies is no saisically significan. 3 METHODOLOGY The empirical resuls presened in his aricle are based he separae esimaion of a valueadded funcion and a wage equaion a he firm level. The value-added funcion yields parameer esimaes for he average marginal produc of each caegory of workers (shor parime workers, long par-ime workers, full-ime workers), while he wage equaion esimaes he respecive impac of each group on he average wage paid by he firm. Esimaing boh equaions wih he same se of conrol variables allows o direcly compare he parameers regarding he marginal produc and he wage of each group of workers. This echnique was pioneered by Hellersein e al. (1999) and refined by Auber and Crépon (2003), van Ours (2009), Göbel and Zwick (2009), van Ours and Soeldraijer (2011), and ohers. Equaion (1) is a funcion linking a range of inpus of firm i o is added value Y i. Yi F( K i, QLi ) (1) where K i represens he firm's capial sock and QL i is a qualiy of labour erm. The laer allows inroducing a heerogeneous labour force ino he value-added funcion. There is an abundan economeric lieraure on he esimaion of relaionships as he one depiced in Equaion (1). Various auhors have proposed differen specificaions, allowing e.g. for differen elasiciies of subsiuion beween he facors of producion, in order o reflec more accuraely he producion process inside he firm. However, our focus is no on he producion process iself, bu raher on he comparison beween produciviy and wage for differen ypes of workers. We herefore use a simple Cobb-Douglas version of Equaion (1), wih subsiuion elasiciies equal o one and he assumpion of firms operaing a he 9
efficiency fronier. Such assumpions do no appear problemaic as previous firm-level sudies have shown ha produciviy coefficiens obained wih a Cobb-Douglas srucure are robus o oher funcional specificaions (see, e.g. Hellersein and Neumark, 2004). Equaion (2) is he basic (Cobb-Douglas) value-added funcion: log( Yi ) log( Ai ) log( Ki ) log( QLi ) (2) where A i is a consan. The parameers α and β are he respecive marginal produciviies of each inpu facor. QL i can be wrien as: G Li, j QL i Li 1 ( j 1) (3) j1 Li where L i is he oal labour force of he firm i and L j /L i he proporion of group j in he oal labour force. In our case, each group j includes all individuals on he same working ime arrangemen (i.e. shor par-ime, long par-ime, full-ime work). Subsiuing Equaion (3) ino (2) allows for differen marginal produciviies for each of he G working ime caegories. If for group j he parameer θ j is bigger (smaller) han uniy, hen his group has a higher (lower) marginal impac on produciviy han he reference caegory, which, in our case, conains all individuals working 35 or more hours per week (i.e. all full-ime workers). If all groups have s equal o one, hen Equaion (3) becomes QL i = L i, i.e. labour is perfecly homogeneous. As for he wage equaion, Auber and Crépon (2003) show ha he average wage of firm i can be expressed as: wi G w j 1 G j 1 j L L j j w 0 G j 1 w w j 0 L j L i wi,0 G w j Li, j 1 1 (4) j {0} wi,0 Li where w j is he average wage of L j and j = 0 he reference working ime caegory wih he wage w 0. Similar o he inerpreaion of θ in he producion funcion, if he raio w j /w 0 is bigger (smaller) han uniy, hen he marginal impac of group j on he average wage in he firm is higher (lower) compared o he reference caegory. Comparing marginal produciviies 10
and wage differenials across groups boils down o comparing j wih he corresponding w j /w 0. 4 DATA AND DESCRIPTIVE STATISTICS Our empirical analysis is based on a combinaion of wo large daa ses covering he years 1999-2006. The firs, carried ou by Saisics Belgium, is he Srucure of Earnings Survey (SES). I covers all firms operaing in Belgium ha employ a leas 10 workers and wih economic aciviies wihin secions C o K of he NACE Rev. 1 nomenclaure. 1 The survey conains a wealh of informaion, provided by he managemen of firms, boh on he characerisics of he laer (e.g. secor of aciviy, number of workers, level of collecive wage bargaining) and on he individuals working here (e.g. age, educaion, enure, gross earnings, paid hours, sex, occupaion). 2 The SES provides no financial informaion. Therefore, i has been merged wih a firm-level survey, he Srucure of Business Survey (SBS). The SBS, also conduced by Saisics Belgium, provides informaion on financial variables such as firmlevel value added and gross operaing surplus per hour. The coverage of he SBS differs from he SES in ha i does no include he whole financial secor (NACE J) bu only Oher Financial Inermediaion (NACE 652) and Aciviies Auxiliary o Financial Inermediaion (NACE 67). The merger of he SES and SBS daases has been carried ou by Saisics Belgium using firms social securiy numbers. 1 I hus covers he following secors: i) mining and quarrying (C), ii) manufacuring (D), iii) elecriciy, gas and waer supply (E), iv) consrucion (F), v) wholesale and reail rade, repair of moor vehicles, moorcycles and personal and household goods (G), vi) hoels and resaurans (H), vii) ranspor, sorage and communicaion (I), viii) financial inermediaion (J), and ix) real esae, rening and business aciviies (K). 2 The SES is a sraified sample. The sraificaion crieria refer respecively o he region (NUTS-groups), he principal economic aciviy (NACE-groups) and he size of he firm. The sample size in each sraum depends on he size of he firm. Sampling percenages of firms are respecively equal o 10, 50 and 100 percen when he number of workers is lower han 50, beween 50 and 99, and above 100. Wihin a firm, sampling percenages of employees also depend on size. Sampling percenages of employees reach respecively 100, 50, 25, 14.3 and 10 percen when he number of workers is lower han 20, beween 20 and 50, beween 50 and 99, beween 100 and 199, and beween 200 and 299. Firms employing 300 workers or more have o repor informaion for an absolue number of employees. This number ranges beween 30 (for firms wih beween 300 and 349 workers) and 200 (for firms wih 12,000 workers or more). To guaranee ha firms repor informaion on a represenaive sample of heir workers, hey are asked o follow a specific procedure. Firs, hey have o rank heir employees in alphabeical order. Nex, Saisics Belgium gives hem a random leer (e.g. he leer O) from which hey have o sar when reporing informaion on heir employees (following he alphabeical order of workers names in heir lis). If hey reach he leer Z and sill have o provide informaion on some of heir employees, hey have o coninue from he leer A in heir lis. Moreover, firms ha employ differen caegories of workers, namely managers, blue- and/or whie-collar workers, have o se up a separae alphabeical lis for each of hese caegories and o repor informaion on a number of workers in hese differen groups ha is proporional o heir share in oal firm employmen. For example, a firm wih 300 employees (namely, 60 managers, 180 whie-collar workers and 60 blue-collar workers) will have o repor informaion on 30 workers (namely, 6 managers, 18 whie-collar workers and 6 blue-collar workers). For more deails see Demuner (2000). 11
Two filers have been applied o he original daa se. Firsly, we deleed firms ha are publicly conrolled and/or operaing in predominanly public secors from our sample. This filer derives is raionale from neoclassical produciviy heory, which relies on he assumpion ha prices are economically meaningful. All regressions are herefore applied o privaely conrolled firms only. 3 Secondly, we have eliminaed firms wih less han 10 observaions. The reason for his is ha we use average values a he firm level. In order o ascerain ha averages are based on a minimum number of observaions, we filered ou firms ha provided informaion on less han 10 employees. 4 Our final sample consiss of an unbalanced panel of 9,225 firms yielding 20,537 firmyear-observaions during he six year period (1999-2006), he exac number depending on he esimaion mehod adoped. I is represenaive of all firms employing a leas 10 employees wihin secions C o K of he NACE Rev. 1 nomenclaure, wih he excepion of large pars of he financial secor (NACE J) and almos all he elecriciy, gas, and waer supply indusry (NACE E). However, given ha he sampling percenages of firms in our daa se increase wih he size of he laer, medium-sized and large firms are over-represened in economeric specificaions requiring firm informaion on several consecuive years. The definiion of earnings we use in he esimaion corresponds o he oal gross wages, including premia for overime, weekend or nigh work, performance bonuses, commissions, and oher premia. The work hours correspond o he oal effecive remuneraed hours in he reference period (including paid overime hours). The firm's value added per hour is measured a facor coss and calculaed wih he oal number of hours effecively worked by he firm's employees. All variables in he SES-SBS are no self-repored by he employees bu provided by he firm's managemen and herefore more precise compared o employee or household surveys. The hresholds we use o disinguish beween differen working ime regimes correspond o widely used pracice in he lieraure. This being said, several definiions of par-ime work exis. According o he ILO Par-Time Work Convenion (1994; No. 175), a par-ime worker is an employed person whose normal hours of work are less han hose of comparable full-ime workers, where he normal hours of work referred o may be calculaed weekly or on average over a given period of employmen. By he same oken, many auhors define par ime wih reference o naional sandard of full-ime working hours (Bardasi and 3 More precisely, we eliminae firms for which public financial conrol exceeds 50%. This exclusion reduces he sample size by less han 4%. 4 This selecion is unlikely o affec our resuls as i leads o a small drop in sample size. 12
Gornick 2008; Manning and Perongolo 2008). By conras, some sudies rely on subjecive self-assessmen o disinguish differen work regimes (OECD, 2010). Wha is more, he definiion of wha consiues par-ime work migh also vary across secors and occupaions. In Belgium, he naional sauory maximum working scheme consiss of 38 hours per week and 8 hours per day. However, hese hresholds are collecive renegoiaed by social parners in mos indusries and/or firms. As a resul, acual sauory maximum working hours are much closer o 35 hours per week and 7 hours per day. Working hours ha exceed hese hresholds are ypically reaed as overime. Par-ime work is defined as regular and volunary work ha is shorer han hese hresholds. I canno be shorer han hree successive hours and, on a weekly basis, no less han a hird of he working ime of a full-ime worker (O Dorchai and Meulders 2009). In line wih sandard pracice, we defined par-ime work as less han 35 hours per week (as similar approach has been adoped in e.g. in Booh and Wood 2008; Rodgers 2004; Hirsch 2005). Ye, pas research has highlighed considerable heerogeneiy among par-ime workers (Hirsch 2005; O Dorchai e al. 2007; Russo and Hassink 2008). For insance, he repercussions of par-ime arrangemens migh differ according o wheher he individual is absen during much of he work week (e.g. an employee wih peripheral asks coming in only one or wo days a week) or wheher she is almos working full ime (e.g. an employee ha works like her full-ime colleagues during he enire week bu leaves he office on Friday noon). In order o capure hese differences, we defined hree groups of individuals: up o 25 hours (shor par imers); beween 25 and 35 hours (long par imers); and 35 or more working hours per week (full imers). 5 [Inser Table 1 here] Table 1 ses ou he means and sandard deviaions of seleced variables. We observe ha firms have a mean value added per hour worked of 57.77 Euros and ha workers mean gross hourly wage sands a 16.76 Euros. In all, 16 per cen of oal hours are accumulaed among people working up o 25 hours per week, 6 per cen of hours are due o he group beween 25 and 35 hours per week, and 78 per cen of hours are worked by people wih 35 hours or more 5 The proporion of workers receiving paymens for over-ime hours is relaively limied in our sample. Moreover, he mean number of over-ime hours among hese workers is generally no very large. Ye, robusness ess have been performed (no repored in he paper due o space consrains bu available upon reques) o make sure ha economerics resuls repored in secion 5.2 are no biased do o he misclassificaion of workers in he long par-ime or full-ime caegories due o he inclusion of overime hours. 13
per week. We also find ha 57 per cen of hours are worked by blue collar workers 6, 36 per cen of hours by people wih a low level of educaion (i.e. lower or lower secondary educaion a mos), and 4 per cen of hours by people on non-sandard employmen conracs. Overall, 65 per cen of workers in our sample are employed in relaively big firms (i.e. firms wih a leas 100 employees) and are essenially concenraed in he manufacuring secor (52 percen), wholesale and reail rade, repair of moor vehicles, moorcycles and personal and household goods (12 per cen), consrucion (13 per cen) and real esae, rening and business aciviies (12 per cen). 5 SPECIFICATION AND RESULTS 5.1 Funcional specificaions of he model In his secion we describe differen specificaions of he equaions (2) and (4). The model formed by equaions (5) and (6) is our baseline specificaion and similar o he model in Hellersein e al. (1999). The β j (wih j = 1, 2) in equaion (5) is he relaive marginal impac of workers share j on average firm level hourly produciviy [noe ha β j corresponds o θ j - 1 in equaion (3)]. In equaion (6), * j is he relaive marginal impac of workers share j on he * average firm level hourly wage ( j corresponds o w j /w 0-1 in equaion (4)). The erms and * represen he error erms. log log Value Added Hours 1A1 2 A2 X (5) * * * * * Toal Wages Hours A A X 1 1 2 2 (6) The dependen variable in equaion (5) is firm i's hourly value added, obained by dividing he oal value added by he firm i in period by he oal number of work hours (aking ino accoun paid overime hours) ha have been declared for he same period. The dependen variable in equaion (6) is firm i's average hourly gross wage (including premia for overime, weekend or nigh work, performance bonuses, commissions, and oher premia). I is obained by dividing he firm's oal wage bill by he oal number of work hours. Hence, he 6 Blue-collar occupaions include Craf and relaed rades workers, Plan and machine operaors, and assemblers, and Elemenary occupaions. 14
dependen variables in he esimaed equaions are firm averages of value added and wage on an hourly basis. The independen variables are also measured in erms of shares in oal work hours (which means ha par-ime shares are measured in erms of he proporion of hours worked by par-ime workers over he oal amoun of hours worked wihin he firm). The main variables of ineres are he shares of hours worked by each of our hree working ime caegories, ( A 1 i,, A 2 i,, A i, 3 ): up o 25 hours per week (shor par ime), beween 25 and 35 hours per week (long par ime) and more han 35 hours per week (full ime); we consider he share of full-ime workers ( A i, 3 ) as our reference caegory. 7 In addiion o he shares in oal work hours, we also included he vecor X. I conains a se of variables conrolling for observable characerisics of he firm and is labour force. More precisely, i includes four dummies for he size of he firm (i.e. he number of employees), respecively four and eigh dummies for he educaional and occupaional composiion of he workforce, he proporion of female employees, four dummies for workers age (beween 15 and 29, beween 30 and 44, beween 45 and 59 and over 60 years), he fracion of workers wih a fixed-erm employmen conrac and eigh dummies for he years of observaions. Since he firms capial sock is no available in he SES-SBS daa se, capial is proxied wih dummy variables for nine economic secors a he one-digi level of he NACE nomenclaure. This is likely o compensae for he omission of capial since he laer ends o be correlaed wih he ype of aciviy of he firm. Moreover, van Ours and Soeldraijer (2011) argue on he basis of previous sudies ha including or no including capial sock doesn seem o affec he parameer esimaes of producion funcions based on firm-level micro survey daa (see also Hellersein e al. 1999; Auber and Crépon 2003; Dosie 2011). 8 Esimaing equaions (5) and (6) allows o gauge he effec of differen working paerns on firm produciviy and wages, bu i does no allow o es direcly wheher he difference beween he value added and he wage coefficiens for a given group of workers is saisically significan. A simple mehod o obain a es for he significance of produciviywage gaps has been proposed by van Ours and Soeldraijer (2011). We apply a similar approach and esimae a model in which he difference beween firm i's hourly value added and hourly wage is regressed on he same se of explanaory variables as in equaions (5) and 7 As highlighed earlier, resuls repored in his paper are robus o he inclusion or exclusion of over-ime hours. 8 For he modaliies of all conrol variables and corresponding descripive saisics see able 1. 15
(6). This produces coefficiens for he wo par-ime groups and measures direcly he size and significance of heir respecive produciviy-wage gaps. We have esimaed equaions (5) and (6), as well as he produciviy-wage gap, wih hree differen mehods. The baseline regression is a pooled Ordinary Leas Squares (OLS) esimaor wih robus sandard errors (we use a Huber/Whie/sandwich esimae of variance, i.e. he errors are robus o heeroscedasiciy and serial correlaion (see Wooldridge 2002)). This esimaor is based on boh he cross-secion variabiliy beween firms and he longiudinal variabiliy wihin firms over ime. Pooled OLS esimaors of value added models have been criicized for heir poenial heerogeneiy bias (Auber and Crépon 2003: 116). This bias is due o he fac ha firm produciviy depends o a large exen on firm-specific, ime-invarian characerisics ha are no measured in micro-level surveys. As a consequence, he working ime coefficiens of hese esimaors migh be biased since unobserved firm characerisics may affec simulaneously he firm's level of value added (or wage) and is workforce composiion. This is referred o as a problem of spurious correlaion and could be caused by facors such as an advanageous locaion, firm-specific asses like he ownership of a paen, or oher firm idiosyncrasies. One way o deal wih unobserved ime-invarian heerogeneiy of firms is o reformulae equaions (5) and (6) as follows: log log Value Added Hours 1A1 2 A2 X i (7) * * * * * Toal Wages Hours A A X 1 1 2 2 i (8) where i is a dummy variable for each firm ha capures ime-invarian individual unobserved characerisics. In order o remove unobserved firm characerisics ha remain unchanged during he observaion period we use a fixed-effec model. Nex, he model is esimaed using he dynamic sysem GMM esimaor proposed by Arellano and Bover (1995) and Blundell and Bond (1998). Such esimaor allows us o address he endogeneiy of our explanaory variables. 9 Share of par imers are likely o be endogenous for several reasons: firsly, workers migh choose or accep o work eiher par ime or full ime according o heir degree of job commimen; secondly, any shock in wages or in produciviy levels migh generae correlaed changes in he firm s workforce and in 9 Technically, variables in he differenced equaion are insrumened by heir lagged levels and variables in he level equaion are insrumened by heir lagged differences. 16
labour produciviy ha are no due o changes in he firm s workforce composiion per se: for insance, in periods of cyclical downurn firms migh reduce workers ime schedules in order o save on labour coss. Furhermore, he dynamic GMM esimaor allows us o conrol for he poenial pah dependency of firm-level produciviy and wages. To his end, we add a one year lag of he dependen variables in Equaions (5) and (6) o he se of explanaory variables: log log Value Added Hours i, logvalue Added Hours 1 1 A1 2 A2 X i (9) * * * * * * Toal Wages Hours i, logtoal Wages Hours 1 1 A1 2 A2 X i (10) 5.2 Esimaion resuls We firs esimae Equaions (5) and (6), as well as he produciviy wage gap wih pooled OLS. In he firs esimaion we do include neiher worker nor firm conrols. Focusing a firs on he produciviy equaion, Table 2 shows ha shor par imers and long par imers are significanly less producive han full imers. Indeed, he regression coefficien associaed wih shor par ime is equal o -1.16 and he coefficien associaed o long par ime is equal o -0.19. This means ha if he fracion of long par-ime workers wihin a firm increases by one uni (i.e. one percenage poin), produciviy decreases on average by 0.19 per cen (i.e. - 0.19 * 0.01 = -0.0019 = 0.19 per cen) and if he fracion of workers working shor par ime increases by one percenage poin produciviy decreases by 1.16 per cen. Regression coefficiens can hus be roughly inerpreed as elasiciies beween produciviy and group shares. Ye, one should keep in mind ha a change in one group of (shor par-ime, long parime or full-ime) workers modifies he incidence of workers in oher groups. Turning o he relaionship beween par ime and wages, resuls show ha a one percenage poin increase in shor par imers decreases mean hourly wages wihin firms by 0.71 per cen and ha mean hourly wage decreases by 0.08 per cen following a one percenage poin increase in he fracion of long par imers. The comparison of esimaes for he produciviy and wage equaions suggess ha he produciviy-wage gap is negaive for boh shor and long par ime. This means ha, according o OLS esimaes, he wo caegories are overpaid. Resuls from he produciviy-wage gap regression suppor his finding. Indeed, he impac of shor par-ime and long par-ime workers on he produciviy-wage gap is found o be significanly negaive (-0.44 and -0.11 respecively). 17
Inroducing worker and firm conrols in he regression modifies resuls as follows. As o he produciviy equaion, he sign of he coefficiens remains he same bu heir magniude is reduced: he coefficien for shor par ime drops o -0.40 and he coefficien for long par ime o -0.08. Considering he wage equaion, he righ par of Table 2 illusraes ha a relaive increase in shor par imers reduces mean hourly wages by 0.10 per cen and an increase in he share of long par imers increases i by 0.07 per cen. Turning o he produciviy-wage gap, resuls are in line wih he previous ones: boh shor and long par imers are found o be overpaid (he respecive coefficiens are -0.30 and -0.15). [Inser Table 2 here] Findings repored so far should be inerpreed wih cauion given ha hey are subjec o several mehodological limiaions. In paricular, ime-invarian unobserved workplace characerisics are no accouned for. The Breusch and Pagan (1980) Lagrangian muliplier (10441.58 for he value added and 10218.84 for he wage equaion) indicaes ha we have o refue he adequaeness of pooled OLS for he esimaion of equaions (5) and (6). In addiion, he Hausman es (894.50 for he value added and 1792.59 for he wage equaion) calls for a fixed-effecs model. Resuls based on a fixed-effec esimaor are repored in Table 3 and subsanially differ from OLS resuls. Regarding he value added equaion, findings (no conrolling for he lagged dependen variable) show ha he share of par imers does no affec average produciviy a he firm level since boh he coefficiens for shor par ime and long par ime are posiive bu no significan (0.03 and 0.01, respecively). As o he wage equaion, he coefficien for shor par ime urns ou o be posiive and equal o 0.13, while he coefficien for long par ime remains posiive bu decreases o 0.05. Findings for he produciviy-wage gap equaion show ha he gap is negaive and significan boh for shor par ime (-0.11) and for long par ime (-0.04). Overall, once fixed effecs are aken ino accoun, resuls sill indicae ha shor and long par ime workers are slighly overpaid, bu we do no find any negaive effec of par ime workers on average firm level produciviy. 10 [Inser Table 3 here] 10 Resuls are quie similar if he lagged dependen variable is conrolled for (see he las hree columns of Table 3), excep ha he produciviy-wage gap for long par ime is only significan a he 15 percen level. 18
Ye, i could sill be argued ha fixed-effecs esimaes are biased and inconsisen due o he endogeneiy of he shares of shor and long par-ime workers. To address his issue, conrolling a he same ime for firm fixed effecs and he sae dependency of firm produciviy and wages, we esimae our model using he dynamic sysem GMM esimaor proposed by Arellano and Bover (1995) and Blundell and Bond (1998). To examine he reliabiliy of he corresponding esimaes, we firs apply he Hansen (1982) es of overidenifying resricions and he Arellano-Bond s (1991) es for second-order auocorrelaion in he firs-difference errors. As shown in Table 4, hey respecively do no rejec he null hypohesis of valid insrumens and of no auocorrelaion. As expeced, we also find ha curren produciviy and mean wages a he firm level are significanly relaed o heir pas values. [Inser Table 4 here] Furhermore, esimaes of he value added equaion show a posiive (0.01) bu insignifican coefficien for shor par ime and a posiive (0.14) and significan coefficien for long par ime. Conrary o he heory of sar-up coss (Barzel 1973), our esimaes hus sugges ha par ime can be beneficial for firm produciviy, a leas if i exceeds 25 hours per week. In oher words, i appears ha cerain par imers perform he equivalen of full-ime jobs bu wihin slighly fewer hours. This inerpreaion is suppored by he lieraure arguing ha, for various reasons, many par imers coninue o be confroned wih full-ime workloads (Lewis 2001; Lewis 2003; Edwards and Robinson, 2000; Sanworh 1999). Ye, oher heoreical explanaions (e.g. reciprociy heories; he appropriaeness of par ime in ligh of he circadian rhyhm; or end-of-he-day faigue) are also in line wih our resuls for long par ime. As o he wage equaion, neiher he shor nor he long par-ime coefficien (0.05 and 0.02, respecively) is significanly differen from zero. Resuls hus indicae ha here is no par-ime wage gap in he Belgian privae secor when conrolling for a large number of worker and firm characerisics (including firm fixed effecs) and endogeneiy issues. Finally, findings from he produciviy-wage-gap regression indicae ha shor par imers are paid a heir marginal produciviy (he coefficien is negaive (-0.04) bu no significan), whereas long par-imers would be underpaid (he coefficien is significan and equal o 0.12). Resuls for he produciviy-wage gap, consisen wih hose obained separaely on he basis of produciviy and wage regressions, sugges ha ani-discriminaory policies on he Belgian labour marke are more effecive o proec shor han long par-ime workers. 19
6 CONCLUSION During he las wo decades, par ime has become one of he main vecors of labour marke flexibiliy in Europe and elsewhere. I has also risen sharply during he recen economic downurn (Employmen in Europe 2010). In OECD counries, on average one in four women and one in en men work par ime (OECD 2010). A growing lieraure examines he impac of working ime on workers wages. Empirical resuls ypically documen a significan gap beween hourly wages of par- and fullime workers. By and large, his gap has been aribued o subsanial heerogeneiy beween jobs and/or beween individuals (Hirsch, 2005; Manning and Perongolo, 2008). Ye, for some counries a significan fracion of his gap remains unexplained afer conrolling for observable heerogeneiy. This may poin o oher forms of labour marke inequaliy or discriminaion agains par-ime workers (Bardasi and Gornick 2008). Besides, few sudies have focused on produciviy differences beween full-ime and par-ime workers. In fac, he relaionship beween working hours and produciviy has no been clearly esablished: boh exan heory and empirical resuls are inconclusive (Branine 2003; Lewis 2003; Nelen e al. 2011). Finally, as far as we know, here are no sudies invesigaing wheher par-ime workers are paid a heir marginal produciviy using accurae informaion on boh wages and produciviy. The presen paper conribues o his lieraure by esimaing he effec of par-ime work on produciviy, wages and produciviy wage-gaps. More precisely, we are among he firs o compare he produciviy and wage profiles of hree groups of workers: hose working less han 25 hours (shor par ime), beween 30 and 35 hours (long par ime), and more han 35 hours per week (full ime). To do so, we used deailed longiudinal mached employeremployee daa covering he Belgian privae secor over he period 1999 2006. Our daa allows o ackle a range of measuremen issues ha have no been addressed in he exising lieraure: he panel daa provides precise informaion on average produciviy and wages wihin firms; conrols for a wide range of worker and firm characerisics; and permis o deal wih ime-invarian unobserved firm heerogeneiy, he endogeneiy of par-ime shares, and he sae dependence of firm produciviy and wages. The disincion beween shor and long par-ime workers, oo ofen negleced in he lieraure, is an imporan feaure of our sudy (Hirsch 2005; Russo and Hassink 2008). Indeed, he repercussions of par-ime arrangemens on wages and produciviy are likely o differ according o wheher he individual is absen during much of he work week (e.g. an employee wih peripheral asks coming in only one or 20
wo days a week) or wheher she is almos working full ime (e.g. an employee ha works like her full-ime colleagues during he enire week bu leaves he office on Friday noon). Resuls from our preferred specificaion, based on he dynamic sysem GMM esimaor, indicae ha average hourly wages wihin firms do no significanly depend on he incidence of shor and long par-ime workers. They hus highligh he absence of any parime wage gap. Neverheless, resuls from he OLS model show ha wage penalies associaed o shor par ime employmen are explained by differences in individual and job characerisics, meaning ha individuals working less han 25 hours per week are concenraed in low-paid jobs. This segregaion effec is less apparen for long par imers (he gross wage differenials in he OLS model is much smaller for his group). Regarding produciviy, GMM resuls indicae ha a marginal increase in he share of shor par-ime workers does no affec average firm produciviy. This could mean ha he negaive and posiive effecs of shor par ime on produciviy ha have been hypohesised in he heoreical lieraure eiher cancel each oher or simply don' exis. On any accoun, shor par ime seems o be paid a marginal produciviy and we find no signs of wage discriminaion for his group. This resul migh be aribued o Belgium's relaively effecive ani-discriminaion policies ha srive o proec par-ime workers. As regards par ime jobs ha exceed 25 weekly working hours, however, GMM esimaions indicae ha a marginal increase in he share of long par ime has a posiive effec on firm produciviy and we find ha his group is paid below is marginal produciviy. Overall, our empirical resuls sugges ha par ime has no srongly derimenal effec on firm produciviy. For par-ime jobs wih more han 25 weekly work hours he opposie seems o be he case. We argued ha his could be due o workers in long par-ime jobs facing wha are effecively full-ime workloads. In oher words, individuals ha work almos full ime are effecively carrying ou full-ime jobs in par-ime hours, for insance due o managemen no aking ino accoun working ime reducions when esablishing work plans or performance expecaions (Sanworh 1999; Edwards and Robinson, 2000; Lewis 2001, 2003). I should be noed, however, ha oher heoreical explanaions are also in line wih our resuls (e.g. reciprociy heories; he appropriaeness of par ime in ligh of he circadian rhyhm; or end-of-he-day faigue). 21
REFERENCES Arellano, Manuel, and Bond Sephen. 1991. Some Tess of Specificaion for Panel Daa: Mone Carlo Evidence and an Applicaion o Employmen Equaions. Review of Economic Sudies 58(2): 277-97. Arellano, Manuel, and Bover Olympia. 1995. Anoher look a insrumenal variables esimaion of error-componen models. Journal of Economerics 68(1): 29 51. Arvaniis, Spyros. 2003. Numerical and Funcional Labour Flexibiliy a Firm Level: Are There Any Implicaions for Performance and Innovaion? Evidence for he Swiss Economy, KOF-Arbeispapiere/Working papers no. 80. Sepember, Zurich. Auber, Parick, and Bruno Crépon. 2003. La producivié des salariés âgés: une enaive d esimaion. Economie e Saisique, 368: 95-119. Bales, Boris. B., Briggs, Thomas E., Huff, Joseph W., Wrigh, Julie A. and Neuman, George A. 1999. Flexible and compressed workweek schedules: A mea-analysis of heir effecs on work-relaed crieria. Journal of Applied Psychology, 84(4): 496 513. Bardas Elena, and Gornick, Jane C. 2008. Working for Less? Women's Par- Time Wage Penalies Across Counries. Feminis Economics, 14(1): 37-72. Barzel, Yoram. 1973. The Deerminaion of Daily Hours and Wages. Quarerly Journal of Economics, 87(2): 220 238. Blundell, Richard, and Bond Sephen. 1998. Iniial condiions and momen resricions in dynamic panel daa models. Journal of Economerics, 87(1): 115-143. Bonamy, Joel, and May Nicola. 1997. Service and Employmen Relaionship. The Services Indusries Journal, 17(4): 544-563. Booh, Alison, and Wood Margi. 2008. Back-o-fron down-under? Par-ime/full-ime wage differenials in Ausralia. Indusrial Relaions, 47(1): 114-135. Branine, Mohamed. 1999. Par ime work in he public healh service of Denmark, France and he UK. Inernaional Journal of Human Resource Managemen, 10(3): 411 429. Branine, Mohamed. 2003. Par-ime work and job sharing in healh care: Is he NHS a familyfriendly employer?. Journal of Healh Organizaion and Managemen, 17(1): 53-68. Breusch, Trevor, and Pagan, Adrian R. 1980. The LM es and is applicaion o model specificaion in economerics. Review of Economic Sudies, 47(1): 239 254. Brewser, Chris, Hegewisch, Ariane, and Mayne Lesley. 1994. Flexible working pracices: he conroversy and he evidence. In Brewser Chris, Hegewisch Ariane, (Eds), Policy and 22
Pracice in European Human Resource Managemen: The Price Waerhouse Cranfield Survey. Rouledge, London. Demuner, Chrisophe. 2000. Srucure and disribuion of earnings survey: Analysis 1995. Saisics Belgium Working paper, Brussels. Dosie, Benoi. 2011. Wages, produciviy and aging. De Economis, 159(32): 139-158. Edwards, Chrisine and Robinson Olive. 2000. Managing par-imers in he police service: A sudy of inflexibiliy. Human Resource Managemen Journal, 9(4): 5-18. Edwards, Chrisine and Robinson Olive. 2004. Evaluaing he Business Case for Par-ime Working amongs Qualified Nurses. Briish Journal of Indusrial Relaions, 42(1): 167 183. Employmen in Europe 2010, Direcorae-General for Employmen, Social Affairs and Equal Opporuniies, European Commission. Ermisch, John F., and Wrigh, Rober E. 1991.Wage offers and full-ime and par-ime employmen by Briish women. Journal of Human Resources, 25(1): 111-33. Göbel, Chrisian and Zwick, Thomas. 2009. Age and produciviy - Evidence from linked employer employee daa. ZEW Discussion Paper no. 09-020, Mannheim. Hagemann, Helmu, Sommerfeldl Klaus, Dingier Markus, Miiffer Wolfgang, Neuberger Clans and Delker Chrisel. 1994. Divide o Win: The Poenial in Flexible Par-ime Work, McKinsey & Company. Hansen, Lars. 1982. Large Sample Properies of Generalized Mehod of Momens Esimaors. Economerica, 50(4), 1029-54. Hardoy, Inés and Schøne Pål. 2006. The par-ime wage gap in Norway: How large is i really?. Briish Journal of Indusrial Relaions, 44(2): 263-82. Hellersein, Judih K., Neumark David and Troske, Kenneh R. 1999. Wages, produciviy and worker characerisics: Evidence from plan-level producion funcions and wage equaions. Journal of Labor Economics, 17(2): 409-446. Hellersein, Judih K., and Neumark David. 2004. Producion funcion and wage equaion esimaion wih heerogeneous labor: Evidence from a new mached employer-employee daa se. NBER Working Paper no. 10365, Cambridge, MA. Hirsch Barry, T. 2005. Why do par-ime workers earn less? The role of worker and job skills. Indusrial and Labor Relaions Review, 58(4): 525-551. Jepsen, Maria. 2001. Evaluaion des différeniels salariaux en Belgique: hommes femmes e emps pariel emps plein. Refles e perspecives de la vie économique, XL(1-2): 51-63. 23
Koskela, Erkki and Ronnie Schöb. 1999. Does he composiion of wage and payroll axes maer under Nash bargaining?. Economics Leers, 64(3): 343-349. Koskela, Erkki and Vilmunen Jouko. 1996. Tax progression is good for employmen in popular models of rade union behavior. Labour Economics, 3(1):65-80. Lewis, Suzan. 2001. Resrucuring workplace culures: The ulimae work family challenge? Women in Managemen Review, 16(1): 21 29. Lewis, Suzan. 2003. Flexible Working Arrangemens: Implemenaion, Oucomes and Managemen. Inernaional Review of Indusrial and Organizaional Psychology, 18: 1-28. Manning, Alan, and Perongolo Barbara. 2008. The Par-Time Pay Penaly for Women in Briain. Economic Journal, 118(526): F28-F51. Meulders, Danièle and O'Dorchai Sile. 2009. Gender and flexibiliy in working ime in Belgium. Working paper DULBEA, Research Repor, N 09-08.RR, March. Mongomery, Mark. 1988. Hours of Par-ime and Full-Time Workers a he Same Firm. Indusrial Relaions, 27(3): 394-406. Nelen, Annemarie, de Grip Andries and Fouarge Didier. 2011. Is Par-Time Employmen Beneficial for Firm Produciviy?. Research Memoranda 002. Maasrich. ROA, Research Cenre for Educaion and he Labour Marke. O Dorcha Sile, Plasman Rober and Rycx Francois. 2007. The par-ime wage penaly in European counries: how large is i for men?. Inernaional Journal of Manpower, 28(7): 571-603. OECD. 2010. Employmen Oulook 2010, Moving Beyond he Crisis. OECD, Paris. Pierce, Jon L., and Newsrom, John W. 1983. The design of flexible work schedules and employee responses: Relaionships and process. Journal of Occupaional Behavior, 4(4): 247-262. Riley, Nicola-Maria. 1997. Deerminans of union membership: a review. Labour, 11(2):265-301. Rodgers, Joan R. 2004. Hourly wages of full-ime and par-ime employees in Ausralia. Ausralian Journal of Labour Economics, 7(2): 231-54. Russo, Giovanni and Hassink, Woler. 2008. The Par-Time Wage Gap: a Career Perspecive. De Economis, 156 (2): 145-174. Shepard, Edward, Clifon, Thomas and Kruse, Douglas. 1996. Flexible work hours and produciviy: Some evidence from he pharmaceuical indusry. Indusrial Relaions, 35(1): 123-139. 24
Skåun, John D. 1998. Divide he hours and conquer he surplus: par-ime workers and pay. Economics Leers, 61(2): 235-42. Savrou, Eleni T. 2005. Flexible work bundles and organizaional compeiiveness: a crossnaional sudy of he European work conex. Journal of Organizaional Behavior, 26(8): 923 947. Sanworh, Celia M. 1999. A bes case scenario? Non-manual par-ime work and job-sharing in UK local govemmen in he 1990s. Communiy, Work & Family, 2(3): 295-310. Van Ours, Jan C. 2009. Will you sill need me: When I m 64?. De Economis, 157(4): 441-460. Van Ours, Jan C. and Soeldraijer, Lenny. 2011. Age, wage and produciviy in Duch manufacuring. De Economis, 159(2): 159-192. Vella, Francis.1993. Nonwage benefis in a simulaneous model of wages and hours: Labour supply funcions of young female. Journal of Labor Economics, 11(4): 704-723. Wooldridge, Jeffrey (2002), Economeric Analysis of Cross Secion and Panel Daa, MIT Press. 25
TABLE 1. DESCRIPTIVE STATISTICS (1999-2006) Variables: Mean Sd. Dev. Added value per hour (2006 Euros) 57.77 525.98 Hourly wage (2006 Euros) 16.76 5.57 Share of workers < 30 years 0.23 0.16 Share of workers beween 30 and 44 years 0.49 0.16 Share of workers beween 45 and 59 years 0.27 0.17 Share of workers >= 60 years 0.01 0.03 Educaion: Lower educaion 0.08 0.17 Lower secondary educaion 0.28 0.30 General upper secondary school 0.19 0.24 Technical/arisic/professional upper secondary school 0.21 0.25 Shor higher educaion 0.15 0.18 Long higher educaion or universiy 0.09 0.15 Occupaions: Managers 0.03 0.08 Professionals 0.10 0.19 Technicians and associae professionals 0.08 0.15 Clerical suppor workers 0.17 0.22 Service and sales workers 0.05 0.19 Craf and relaed rades workers 0.26 0.33 Plan and machine operaors, and assemblers 0.22 0.30 Elemenary occupaions 0.09 0.20 Working ime: Shor Par ime (< 25 work hours per week) 0.16 0.14 Long Par ime (25 o 35 hours per week) 0.06 0.07 Full ime (>= 35 work hours per week) 0.78 0.19 No sandard (i.e. non open-ended) employmen conrac 0.04 0.10 Number of employees per firm: < = 19 0.03 20 o 49 0.14 50 o 99 0.18 100 o 199 0.25 200 o 499 0.26 > = 500 0.14 Secor (%): Mining and quarrying (C) 0.00 Manufacuring (D) 0.52 Elecriciy, gas and waer supply (E) 0.00 Consrucion (F) 0.13 Wholesale and reail rade, repair of moor vehicles, moorcycles and personal and household goods (G) 0.12 Hoels and resaurans (H) 0.02 Transpor, sorage and communicaion (I) 0.08 Financial inermediaion (J) 0.01 Real esae, rening and business aciviies (K) 0.12 Number of observaions 20,537 Number of firms 9,225 26
TABLE 2 POOLED OLS ESTIMATES, 1999-2006 Wihou conrol variables Dependen variable: Value added Mean wage per Value addedwage per hour worked hour worked gap Shor Par-ime (0, 25) -1.16*** -0.71*** -0.44*** (0.04) (0.02) (0.03) Long Par-ime [25, 35) -0.19*** -0.08*** -0.11*** Wih conrol variables a Value added Mean wage per per hour worked hour worked -0.40*** -0.10*** (0.04) (0.02) -0.08** 0.07*** Value addedwage gap -0.30*** (0.04) -0.15*** (0.03) (0.03) (0.02) (0.02) (0.03) (0.01) Sig. model (p-value) 0.00 0.00 0.00 0.00 0.00 0.00 R² 0.06 0.08 0.01 0.25 0.65 0.05 Number of observaions 20,537 20,537 20,537 20,537 20,537 20,537 Number of firms 9,225 9,225 9,225 9,225 9,225 9,225 Noes: ***/**/* significan a he 1, 5 and 10% level. Robus sandard errors are repored beween brackes. a We conrol for workers characerisics ha include he educaional and occupaional composiion of he firm s workforce (4 and 8 caegories, respecively), share of female employees, worker s age (4 caegories), share of non-sandard work conracs and worker s enure. We conrol for firm characerisics ha include size (4 dummies), indusry (8 dummies) and year dummies (7).. 27
TABLE 3 FIXED EFFECTS ESTIMATES, 1999-2006 Wihou lagged dependen variable Dependen variable: Value added Mean wage per Value addedwage per hour worked hour worked gap Value added per hour worked Wih lagged dependen variable Mean wage per hour worked Value addedwage gap Lagged dependen variable 0.11* (0.06) 0.13*** (0.02) 0.08 (0.06) Shor Par-ime (0, 25) 0.03 (0.05) 0.13*** (0.03) -0.11* (0.06) -0.09 (0.08) 0.12*** (0.03) -0.21** (0.09) Long Par-ime [25, 35) 0.01 (0.02) 0.05*** (0.01) -0.04* (0.02) -0.01 (0.03) 0.04*** (0.01) -0.05 (0.03) Sig. model (p-value) 0.00 0.00 0.00 0.00 0.00 0.00 Wihin R² 0.02 0.49 0.00 0.20 0.63 0.02 Number of observaions 20,537 20,537 20,537 6,753 6,753 6,753 Number of firms 9,225 9,225 9,225 2,487 2,487 2,487 Noes: ***/**/* significan a he 1, 5 and 10% level. Robus sandard errors are repored beween brackes. a We conrol for workers characerisics ha include he educaional and occupaional composiion of he firm s workforce (4 and 8 caegories, respecively), share of female employees, worker s age (4 caegories), share of non-sandard work conracs and worker s enure. We conrol for firm characerisics ha include size (4 dummies), firm indusry (8 dummies) and year dummies (7). 28
TABLE 4 DYNAMIC SYSTEM GMM ESTIMATES, 1999-2006 Dependen variable: Value added per hour worked Mean wage per hour worked Lagged dependen variable 0.22** 0.32*** (0.11) (0.08) Shor Par-ime (0, 25) 0.01 0.05 (0.11) (0.05) Long Par-ime [25, 35) 0.14** 0.02 Value addedwage gap 0.20*** (0.05) -0.04 (0.14) 0.12* (0.06) (0.05) (0.03) Sig. model (p-value) 0.00 0.00 0.00 Arellano Bond es for AR(2) (p-value) 0.92 0.51 0.65 Hansen es (p-value) 0.53 0.16 0.45 Number of observaions 6,753 6,753 6,753 Number of firms 2,487 2,487 2,487 Noes: ***/**/* significan a he 1, 5 and 10% level. Robus sandard errors are repored beween brackes. We conrol for worker characerisics ha include he educaional and occupaional composiion of he firm s workforce (4 and 8 caegories, respecively), share of female employees, worker s age (4 caegories), share of non-sandard work conracs and worker s enure. We conrol for firm characerisics ha include size (4 dummies), indusry (8 dummies) and year dummies (7). Firs and second lags of explanaory variables, excluding ime dummies, are used as insrumens. 31